Energy conservation is one of the foremost requirements of today's electronic era. Humanity had moved to automation and mostly depends on various kinds of automated electronic/mechanical system to perform their daily tasks. One of the kinds of such automated systems are systems for controlling electronics devices, lighting sources, other energy consuming devices etc. in a room (or a defined area). Such systems are configured to control the lighting sources and/or other energy consuming devices based on the occupancy of the room (or the defined area). In general, said systems comprises of sensors to detect occupancy of the room and based on occupancy activates/de-activates the electronic devices without any manual intervention and thereby preventing the wastage of energy.
Occupancy detection systems essentially consist of sensors and a controller connected via a network with the sensors in order to control lighting sources and other energy consuming devices based on the occupancy of a room (or a defined area). The sensors detect whether the room (or the defined area) is empty or occupied and pass on the information to the controller which eventually controls the illumination of lighting devices and power of other energy consuming devices.
In such systems, the efficiency reduces with the increased area, say for example big rooms, conference rooms, office space, meeting halls etc., as only a small portion of the room is occupied most of the time. In such situations, the optimal energy saving strategy should be to slowly dim (or switch off) the lights (or other energy consuming devices) in the unoccupied area. However, such disclosed systems are not able to perform desired functions due to lack of optimized functioning of the system in relation to occupancy location of the defined area.
In order to overcome the aforesaid shortcomings of typical occupancy detection systems, occupancy location systems had been developed over the time. In such systems, sensor measurements of conventional high resolution video camera and high computational resources were used to determine occupancy location. Hence, said systems were not cost effective and require maintenance.
Further, conventional occupancy location systems are upgraded by using coded aperture cameras instead of classical lens based cameras. The coded aperture cameras are much cheaper, have larger field of view and maintenance free. Coded aperture camera with reduced number of photo sensors, also known as compressive coded aperture camera is much cheaper and has several desirable properties. However, the measurements from the said coded aperture camera require much complex processing as compared to the lens based cameras.
In general, the coded aperture camera is similar to a pin hole camera, however the aperture of the compressive coded aperture camera is made of multiple pin holes. Thus the coded aperture camera has better signal-to-noise ratio to a classical pin hole camera.
Although the coded aperture camera have advantages over the conventional lens based camera and the pin hole camera, the photo sensor measurements obtained using the coded aperture camera require extensive post processing in order to reconstruct the image. Since compressive coded aperture camera use less number of sensors then the number of pixels in the image, the required post processing is even more extensive.
There are several inventions related to coded aperture camera. However, there are no practical prior methods available for occupancy location using a compressive coded aperture camera. Further, said methods are not suitable for real time implementation using micro-controllers. Few of them are discussed herein below:
In ref. [1] (R. F. Marcia and R. M. Willett. Compressive coded aperture superresolution image reconstruction. In Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on, pages 833-836, IEEE, 2008) special aperture is designed for compressive coded aperture camera, and known algorithm for compressive sensing is used to reconstruct the scene image. However, the method presented in ref. [1] require special aperture design, and the computational complexity is too high for an implementation in a micro-controller.
In ref. [2] (R. Marcia, Z. Harmony, and R. Willett. Compressive coded aperture imaging. In Proc. SPIE Symp. Elec. Imaging: Computer Imaging, San Jose, Calif., 2009) special optical setup is done using a compressive coded aperture camera in order to obtain super resolution images. However, the method described in ref. [2] requires special optical setup, and the computational complexity is too high for an implementation in a micro-controller.
In ref. [3] (N. Jacobs, S. Schuh, and R. Pless. Compressive sensing and differential image-motion estimation. In Acoustics, Speech and Signal Processing (ICASSP), 2010. IEEE International Conference on, pages 718-836, IEEE, 2010) a method is described to process the sensor measurements of compressive coded aperture camera to detect movement or occupancy. However, the method described in ref. [3] requires accurate motion model. The requirement for an accurate motion model makes the method of ref. [3] impractical.
To overcome the above identified limitations of the existing arts there is need for a solution that provides a practical and cost effective occupancy location system, which employs a very fast and memory efficient processing of data, which can utilize the sensor measurements from a compressive coded aperture camera preferably using a 20-50 MHz micro-controller.